Numerical Investigation of Nanoparticle Distribution Strategies in Nano Cryosurgery of Axisymmetric Biological Tissue

Abstract

Cryosurgery is a minimally invasive technique used to destroy tumors by freezing them with extreme cold. However, its effectiveness is limited by the inherently low thermal conductivity of biological tissue, which restricts heat transfer and may result in incomplete tumor ablation or unintended damage to surrounding healthy tissue. This study numerically investigates the use of Magnesium Oxide (MgO) nanoparticles to enhance thermal transport during cryosurgery. MgO nanoparticles are selected due to their relatively high thermal conductivity, chemical stability, biocompatibility, and potential biodegradability, making them suitable for biomedical applications. A two-dimensional axisymmetric computational model of biological tissue containing a tumor was developed in ANSYS Fluent based on the Pennes bioheat equation, incorporating phase change to simulate the freezing process. The effective density, specific heat, and thermal conductivity of nanoparticle-enhanced tissue were calculated using the Maxwell–Eucken model at a 3% volume fraction. Three nanoparticle distribution strategies were analysed nanoparticles dispersed in surrounding tissue, nanoparticles injected directly into the tumor, and nanoparticles present in both regions. The results show that nanoparticle inclusion significantly improves freezing efficiency. The configuration with nanoparticles concentrated in the tumor produces the largest and fastest-forming lethal iceball. These findings suggest that increasing tumor thermal conductivity using MgO nanoparticles enhances cryoprobe performance, shortens freezing time, and improves the precision of cryosurgical treatment.